Multiple Discriminant Analysis Research Articles

Post-transaction Phase of Logistics Customer Service in the Management of Companies Providing Transport Services

Purpose: The research problem of this article is to identify the elements of the post-transaction phase of logistics customer service in companies providing transport services with reference to the size of these entities, as well as examining the impact of selected post-transaction elements of logistics customer service on the faultlessness of the services of the surveyed companies. Design/Methodology/Approach: The questionnaire research made it possible to identify the elements of the post-transaction phase of logistics customer service practiced in the entities, with particular emphasis on the methods of after sales communication. The statistical analysis aimed to achieve the objective of this paper consisted in revealing the relation of post-transaction phase elements and size of the entities. This relationship was indicated by determining the correlation and testing statistical significance. The impact of selected post-transaction elements of logistics customer service on the measure of faultlessness of services of the surveyed companies was also tested, using multiple discriminant analysis. Findings: On the basement on the fragmentary survey results it should be assessed that they are identifiable in the current operations of entities, although their scope is significantly limited. Practical Implications: The research results can be used by managers of transport enterprises to create their logistics customer service strategy. Originality/Value: It is an original research study combining a market research based on questionnaire and multiple discriminant analysis with interesting managerial conclusions.

A new multivariate approach for assessing corporate financial risk using balance sheets

Several indicators and univariate ratios can be used to measure the soundness of firms as reflected in their balance sheets (leverage, profitability, liquidity ratio, etc.). However, each indicator alone cannot measure a firm's overall financial risk or financial distress level. In this study, we measure the financial strength of the real sector firms listed on the Borsa Istanbul (BIST) by producing a composite index score that combines several different corporate finance ratios. In the first section, we conduct a multiple discriminant analysis of the variables used in Altman's z-score (1968), which is the most prevalent composite index used to measure firms' financial risk in the literature. In the second section, we introduce a new index, called the multivariate firm assessment (MFA) score, which uses the ratios that best explain the characteristics of companies listed on the BIST. The Tailored version of the Altman z-score and our new index have predictive power of around 90 percent. Furthermore, the MFA score reflects the impact of macroeconomic developments on firms' balance sheets and thus serves as an early warning of financial distress for Turkish firms. Our analyses using the MFA score suggest that non-exporting firms and firms with an open foreign exchange position have weaker balance sheets.

Limpet (Cellana spp.) shape is correlated with basalt or eolianite coastlines: Insights into prehistoric marine shellfish foraging and mobility in the Hawaiian Islands

Marine molluscs are highly diverse in size, anatomical structure, behaviour, and habitat and can provide information on human foraging, mobility, diet, and palaeoenvironments. Molluscs occupy a variety of substrates including rocky shores, coral reefs, mud flats, and sandy beaches and shell morphology reflects their habitat and mode of life (e.g., mobility, method of feeding, defence against predators). The north windward coast of west Moloka‘i, Hawaiian Islands, consists mostly of smooth basalt boulders, with sections of eolianite (limestone) shoreline. These contrasting littoral shores influence the composition of the rocky shore intertidal mollusc populations, but both support large numbers of the ubiquitous Hawaiian limpet (Cellana exarata, C. sandwicensis, C. talcosa). We investigated if limpet shell shape (i.e., form and dimensions) varied between shoreline types by multi-year sampling of modern mollusc populations on basalt and eolianite coastlines. Using multiple discriminant analysis, modern shell shape was compared to archaeological limpet assemblages from three late prehistoric habitation sites adjacent to basalt and eolianite shorelines. Our results demonstrate that archaeological shell shape correlates to modern limpet shell shape from nearby basalt or eolianite coastlines suggesting low forager mobility during late prehistory.

Extending critical infrastructure element longevity using constellation-based ID verification

This work supports a technical cradle-to-grave protection strategy aimed at extending the useful lifespan of Critical Infrastructure (CI) elements. This is done by improving mid-life operational protection measures through integration of reliable physical (PHY) layer security mechanisms. The goal is to improve existing protection that is heavily reliant on higher-layer mechanisms that are commonly targeted by cyberattack. Relative to prior device ID discrimination works, results herein reinforce the exploitability of constellation-based PHY layer features and the ability for those features to be practically implemented to enhance CI security. Prior work is extended by formalizing a device ID verification process that enables rogue device detection demonstration under physical access attack conditions that include unauthorised devices mimicking bit-level credentials of authorized network devices. The work transitions from distance-based to probability-based measures of similarity derived from empirical Multi-Variate Normal Probability Density Function (MVNPDF) statistics of multiple discriminant analysis radio frequency fingerprint projections. Demonstration results for Constellation-Based Distinct Native Attribute (CB-DNA) fingerprinting of WirelessHART adapters from two manufacturers includes 1) average cross-class percent correct classification of %C > 90% across 28 different networks comprised of six authorized devices, and 2) average rogue rejection rate of 83.4% ≤ RRR ≤ 99.9% based on two held-out devices serving as attacking rogue devices for each network (a total of 120 individual rogue attacks). Using the MVNPDF measure proved most effective and yielded nearly 12% RRR improvement over a Euclidean distance measure.

The Usefulness of Operating Cash Flow for Predicting Business Bankruptcy in Medium-Sized Firms

Purpose – This paper proposes using operating cash flow (OCF) as an instrument to determine a firm’s likelihood of bankruptcy. It presents a new model capable of predicting business failure based on data derived from financial statements. Design/methodology/approach – In this study, logit analysis was employed because of its frequently-cited conceptual advantages relative to multiple discriminant analysis. Through the logistic regression, we identified an integrated function for several ratios, which is useful when assessing whether a firm can be classified as solvent or insolvent in the future. The sample consists of Spanish medium-sized enterprises (MEs) included in the SABI. Findings – We identified an integrated function for several ratios, including information derived from cash flow statements, which is useful when assessing whether a firm can be classified as solvent or insolvent in the future. The analysis suggests the usefulness of taking into account information provided by cash flow statements when making decisions regarding lending to firms and, also, in relation to the acceptable level of leverage that can be assumed by a firm. Originality/value – The model is capable of predicting the probability that a medium-sized firm might have financial problems three years before this occurs, increasing the capacity to take corrective measures.

Biogeochemistry of Household Dust Samples Collected from Private Homes of a Portuguese Industrial City

The main objectives of the present study were to (i) investigate the effects of mineralogy and solid-phase distribution on element bioaccessibility and (ii) perform a risk assessment to calculate the risks to human health via the ingestion pathway. Multiple discriminant analysis showed that the dust chemistry discriminates between indoor and outdoor samples. The solid-phase distribution of the elements in indoor dust indicated that a large proportion of zinc, nickel, lead, copper, and cobalt is associated with an aluminum oxy-hydroxides component, formed by the weathering of aluminum silicates. This component, which seems to influence the mobility of many trace elements, was identified for a group of indoor dust samples that probably had a considerable contribution from outdoor dust. An iron oxide component consisted of the highest percentage of chromium, arsenic, antimony, and tin, indicating low mobility for these elements. The bioaccessible fraction in the stomach phase from the unified BARGE method was generally high in zinc, cadmium, and lead and low in nickel, cobalt, copper, chromium, and antimony. Unlike other potentially toxic elements, copper and nickel associated with aluminum oxy-hydroxides and calcium carbonates were not extracted by the stomach solutions. These trace elements possibly form stable complexes with gastric fluid constituents such as pepsin and amino acid. Lead had a hazard quotient >1, which indicates the risk of non-carcinogenic health effects, especially for children.

Pemodelan Multiple Discriminant Analysis untuk Memprediksi Financial Distress Bank Umum Syariah di Indonesia

The aims of this study is to set financial distress prediction model and to identify the best accuraction and classification from the financial distress prediction model. The objects were 9 Islamic Banks in Indonesia since 2012 to 2017 using Multiple Discriminant Analysis modelling. The variables used financial ratios, consist of ROA, BOPO, Current Assets to Current Liabilities Ratio, NPF, Equity to Total Liabilities, and FDR. The outcome shows that a variable tend to cause an Islamic bank fall into financial distress condition dominantly was NPF ratio. The accuration prediction power with 42 from 42 obervations predicted fall into health bank category were classified correctly (100%), and 2 from 12 Islamic Banks fall into financial distress category were classified incorrectly (16.7%) and were corrected into helath bank category. The classification power created by multiple discriminant analysis was 81.48%.

Estrés financiero en el sector manufacturero de Ecuador

El presente artículo clasifica a las empresas manufactureras del Ecuador en empresas con estrés financiero (ECE) y sin estrés financiero (ESE). Para tal efecto, se clarifica el significado de estrés financiero y el criterio bajo el cual una empresa sería clasificada como ECE o ESE. Además, se recurre a dos modelos ampliamente utilizados en el medio: el análisis discriminante múltiple y la regresión logística, basados en los trabajos previos de Altman y Ohlson, respectivamente. El estudio se enfoca en las empresas del sector manufacturero ecuatoriano durante el periodo 2014-2018. Se destaca que uno de los hallazgos principales es que, en algunos casos, los signos de los coeficientes de los modelos estimados difieren de los modelos originales de Altman y Ohlson. Sin embargo, en ambos casos, las tasas de precisión de este estudio son mayores que las de los modelos originales. Finalmente, se encontró que las microempresas son las quepresentan mayor estrés en sentido financiero.

Geographic origin determination of Brazilian Cannabis sativa L. (Marihuana) by multi-element concentration

The Marihuana Polygon production of Cannabis sativa L. supplies the northeastern region of Brazil and represents 30% of the nation’s market. The international trend of indoor cultivation is also occurring in Brazil, and the Brazilian Federal Police (BFP) has been increasing its apprehension of cannabis seeds sent by mail. The present work aims to assess the utility of the multi-element composition of different cannabis plant parts and soil samples where the plants were cultivated to determine their geographic origin. Statistical tools were applied to classification of marijuana samples from distinct geographic regions within northeastern Brazil, including indoor cultivated samples. The multi-element quantification was determined using inductively-coupled plasma – optical emission spectrometry (ICP-OES), and the data were compared by the Kruskal-Wallis H test, and subsequently, multiple discriminant analysis (MDA). The results of the multi-element concentration of cannabis plant samples were also subjected to a principal component analysis (PCA) and an orthogonal partial least squares discriminant analysis (OPLS-DA). The cannabis plant samples from the Marihuana Polygon could be clearly separated from those cultivated indoors, and the distance between them was detectable. The MDA revealed that phosphorus, calcium, magnesium, selenium, and arsenic concentrations were used as variables for this separation. Our results demonstrate that multi-element composition analysis can be used to indicate the origin or cultivation location of cannabis plants. Routine laboratory analyses consisting of multi-element composition combined with statistical analyses provide a reliable tool by which C. sativa movement, cultivation, and interdiction efforts in Brazil may be assessed.

Digital development for a progressive networked society

Digital development for a progressive networked society

A multiple discriminant analysis of the auditor’s going concern opinion: the case of audit opinions in Italy

Purpose The purpose of this paper is to develop a model for assessing the audit evidence of the going-concern (GC) assumptions underlying the preparation of financial statements. Design/methodology/approach This research analyses 678 audit opinions of Italian listed firms from 2007 to 2016 and uses a multiple linear discriminant analysis to create a GC score, which includes variables suggested by the international standards on auditing (ISA) 570 and by literature on GC. Findings The model provides three cut-off scores which can orient auditors towards issuing the most appropriate GC audit opinions (unmodified opinion, unmodified opinion, which includes emphases of matter, qualified opinion or disclaimer of opinion). Research limitations/implications The development of the model is mainly based on public data and does not assess confidential information that is not disclosed in audit opinions. Practical implications This model can enable auditors to identify the most appropriate GC opinion and align auditor’s opinions in similar circumstances, thereby reducing their reliance on discretion and increasing the reliability of their judgement with a higher degree of accuracy. Moreover, this research lists additional events or conditions that may individually or collectively cast significant doubt on GC assumptions. Originality/value This study goes beyond the traditional decision-making process, apparently binary in nature, between “continuity” and “failure” or between “unmodified” and “modified” opinions. It is conceived to detect the different degrees of uncertainty that affect GC evaluations to orient auditors’ professional judgements.

Morphometric Comparison Between Different Populations of Darkling Beetles “Pimilia nilotica (Coleoptera: Tenebrionidae)” In Egypt

Insects include almost 60% of the described eukaryotic animals worldwide. However, the morphological measurements and assessment of the effects of isolation and habitat still lack many insect groups. The current study aimed to compare the morphometric measurements of dissimilar populations of darkling beetles “Pimelia nilotica” in Egypt. A variable comparison of morphometric variations was taken by a threaded micrometer for six different eco-geographical regions from Egypt fall under the Western Mediterranean Coastal Desert, Western Desert Oases, El-Faiyum Depression, the Eastern Desert, Nile Delta, and South Sinai. Twenty-one morphometric measurements were taken in the currents study. Traits best reminiscent of the excellence of populations were distinguished by cluster analysis, and also by the principal component analysis. The primary and second discriminants scores (score 1 and score 2) recorded 76.4% and 23.8%, respectively, of the full variation in samples. Multiple discriminant analysis disclosed clear morphometric differences between Western Desert, Eastern Desert, El-Faiyum Depression, and South Sinai populations. Traits clarifying the maximum of the changeability among populations were those associated with the morphological estimations.

Usability of Z Score: A Case Study on Peoples Leasing and Financial Services Limited & Bangladesh Industrial Finance Company Limited

This study aims to identify whether or not the Z score is usable enough in doing prediction at the early stage of the financial distress of People’s Leasing and Financial Services (PLFS) and Bangladesh Industrial Finance Company (BIFC). To predict corporate failure, Multiple Discriminant Analysis is an effective solution. Z"-Score by Altman is a widely used model of multiple discriminant analysis. Using the data from 2011 to 2017 of PLFS and 2015-2017 of BIFC, this study applied the Altman Z"-Score Model as well as used SPSS software to analyze the descriptive statistics of the financial information and ratios of both company to know the level of financial distresses and attributes for reaching toward distress level. The analysis was presented in tables. The finding shows that Z"-Score by Altman is usable enough to predict the failure of the firm. The descriptive analysis shows that working capital, retained earnings, and income before interest and tax were negative which could be considered as the reasons for the distressed position. This study contributes by showing the usefulness of the Z score of Altman in emerging countries like Bangladesh. This is significant because early prediction can prevent liquidation which ultimately protects various stakeholders of an organization.

Active Sport Tourism in Europe: Applying Market Segmentation Model Based on Human Values

The purpose of this study was to examine if human values sets indicating basic motivational aspects, shared by active sport participants, could be used for the creation of a specific market segmentation model. While the exploration of motivation scales and sport tourist typologies was vast, although limited to small samples, this research constructed a model that tested its applicability and validity on the large general samples. By using data collections from the European Social Survey, the model allowed comparability between surveyed countries by cross-checking multiple psychosocial and demographic factors. The findings identified four main factors that determine active sport tourist values, while at the same time, multiple-discriminant analysis indicated the existence of three active sport clusters, indicating preferences of different sport tourist segments. Furthermore, the study analyzed potential demand markets according to the geographical distribution of active sport segments. The study confirmed that basic human values play an important role in explaining motivation aspects in sport- and tourism-related choices. Overall, the findings may assist marketers in monitoring changes in preferences of sport participants and focus on specific marketing strategies for different segments.

Why one e‐business adoption model won't fit all firm sizes: The case of Lebanon's e‐service industry

AbstractThis study aims to determine the influential factors for e‐readiness among enterprises in developing countries based on their size. Given the well‐recognized value of e‐readiness in promoting e‐business in developing economies, and based on the Perceived e‐Readiness Model that was previously suggested in the literature, the study considered the impact of internal and external factors by firm size on the adoption of e‐business. Survey data were collected from 276 Lebanese senior managers operating in the e‐service industry, and a multiple discriminant function analysis was used to determine whether a set of variables is effective in predicting the e‐readiness of enterprises in two size categories, that is, large and small to medium enterprises. The study observed that the factors that influence enterprises' e‐business adoption vary depending on the firm's size and that one adoption model does not fit “e‐service firms” of different sizes. Large enterprises are more influenced by managers' commitment and the e‐readiness of supporting industries than their smaller counterparts. The research findings will be of interest to managers, policymakers, and academics in the e‐services industry.

An examination of recreational golfers’ psychological connection, participation behavior, and perceived constraints

The purpose of this study was to examine continued sport participation by linking psychological connection with participation behavior and constraints. Recreational golfers (N = 714) completed a survey based on the Psychological Continuum Model (PCM), leisure constraints, and participation behavior items. Participants were classified into four PCM levels: awareness (n = 51), attraction (n = 133), attachment (n = 357), and allegiance (n = 173). Multiple Discriminant Analysis (MDA) revealed unique characteristics for each PCM level based on participation behavior, where higher PCM levels related to more participation behavior. With respect to constraints, self-confidence and interest were more associated with lower PCM levels and structural and social factors were associated with higher PCM levels. The findings contribute to theory on continued participation in sport and leisure and provide empirical evidence for the PCM and leisure constraints frameworks.

Factores de apariencia, experiencia y socioculturales que son determinantes para la visita a parques ecoturísticos de dos regiones. Caso empírico: del Sol (Méx) y Lužánky (Cz)

El propósito de esta investigación es identificar las diferencias entre factores de percepción e interés que hacen que los turistas visiten parques ecoturísticos bajo un enfoque de multiculturalidad. Para este estudio se tomaron en cuenta dos parques ecoturísticos de dos regiones del mundo, con algunas semejanzas entre sí. Por un lado, el parque ecoturístico de México ubicado en Tonatico, Estado de México, denominado parque del Sol y el otro, llamado parque Lužánky en Brno, República Checa.El trabajo de investigación es de tipo transversal, de panel, no probabilístico y experimental. El tratamiento de los datos fue a través de una técnica multivariada de análisis discriminante múltiple tomando en cuenta 34 variables de experiencias y atracción de destino. Se aplicaron 120 cuestionarios a visitantes en otoño de 2017 e invierno 2018, que permitieron relacionar las características socioculturales, factores de apariencias y experiencias de los usuarios.Como resultado del modelo estadístico aplicado, se identificó que existen diferencias vinculadas con los repertorios culturales, la formación académica, el nivel socioeconómico y el interés por la conservación ambiental. Los factores que mayor impacto se presentaron al visitar un parque ecológico de acuerdo con el modelo planteado fueron, para el caso del parque europeo los visitantes presentan una mayor valoración sobre la infraestructura y equipamiento turístico, mientras que para el caso del parque mexicano se tiene mayor interés en la recreación y su estado civil. Este modelo tiene una capacidad de precisión del 93.3% para predecir patrones que identifican la región visitada por los usuarios de los parques.

Using Multiple Discriminant Analysis to Construct a Statistical Model for Predicting Bank Loan Repay and Default Customers in the Eastern Region of Ghana

Banks that lend to small businesses and individuals need to quickly assess the creditworthiness of prospectiveborrowers so as to reduce the probability of issuing bad loans while attempting to maintain their own profitability. It was for these reasons that credit institutions have made several attempts at modeling and reliably forecasting credit default using numerous statistical approaches. The objective of the study was to develop a model which could be used to identify likely future defaulters. The population for the study was all financial institutions were in the Eastern Region of Ghana. A number of banks that could give the needed data for the study was purposefully chosen and a random sample of 150 customers were randomly selected to provide data on the study variables which include customers’ financial standing, reason to loan, employment and demographic information. The statistical model obtained indicated four important influences - total asset, total income, family size and number of years with current employer as the most discriminating variables between the repay and default group. The validity of the model was confirmed using several diagnostic analytical procedures. The importance of examining a model’s sensitivity and specificity in the context of one’s specific, real-world objectives was also discussed.
 Keywords: Loan repay and default; Creditworthiness; Prospective borrowers; Statistical models in banking; Multiple discriminant analysis.

STOCK SPLIT AND STOCK MARKET REACTION: THE EVIDENCE OF INDONESIAN PUBLIC COMPANY

Purpose of study: Go Public Company can raise funds for its operations through the sale of shares to investors. But if the stock price is too high, it can make the investors are not interested in buying stock. Stock market value can be reduced by the stock-split. This study aims to examine the effect of the stock split on abnormal return, stock price; trading volume and security return variability in the go public company on the Indonesia Stock Exchange.
 Methodology: Researchers use data from 41 companies that were taken by purposive sampling from 2013 to 2016. The hypotheses in this study were tested using a Paired sample t-test. 
 Result: The researcher found that the stock split event causes the difference between the stock price, trading volume and security return variability between before and after the stock split. But the results found that the stock split did not cause any differences between the abnormal return before and after the stock split. 
 Application: The results of this study can provide an overview of the relationship between stock split events with stock prices and stock trading volumes.
 Novelty/Originality of this study: This research using different methods compare with previous, namely multiple discriminant analysis. The multiple discriminant analysis methods are part of the discriminant analysis, which is a multivariate technique that includes the dependence method, namely the presence of variables.

“How Ad Music Attitude-Based Consumer Segmentation Can Help Advertisers”

Audio-visual advertising expenditure in developing countries like India is growing fast. Focusing on the advertising music attitude, global and local advertisers need to look into the musical consumption pattern of potential Indian consumers. Different consumers have different attitudes toward music deployed in the advertising, which they evaluate from the perspective of its fit (with different elements of the advertising); created appeal; utilitarian value. Hence, this study focuses on identifying possible segments of consumers based on their attitude toward advertising music (Aam); ascertaining the difference between segments. Further, this study aims at ascertaining the musical preferences of consumers that may prescribe to substantial managerial implications. To identify segments, cluster analysis was carried out based on Aam . Further, a multiple discriminant analysis (MDA) was conducted to find out the difference between clusters/segments. To identify consumers’ music preferences, respondents were asked to rank their topmost music genre out of ten suggested genres. This research identified three consumer segments based on their Aam: enthusiasts, mainstreams, and non-enthusiasts. Enthusiasts, mainstreams, and non-enthusiasts all prefer advertising music from their favorite artists. The results indicated that the discriminant functions among clusters are significant. Consumer segmentation based on Aam increases ad strategy effectiveness. Enthusiasts have a broad musical preference facilitating the most creativity in ad development and execution. Advertising music budget will determine music choice (preexisting, new, original artist, cover, etc.). Consequently, Aam segmentation would help advertisers to design effective advertising music strategy.